Unfavorable social determinants of health and risk of mortality in adults with diabetes: findings from the National Health Interview Survey.

INTRODUCTION: Understanding the role of social determinants of health as predictors of mortality in adults with diabetes may help improve health outcomes in this high-risk population. Using population-based, nationally representative data, this study investigated the cumulative effect of unfavorable social determinants on all-cause mortality in adults with diabetes. RESEARCH DESIGN AND METHODS: We used data from the 2013-2018 National Health Interview Survey, linked to the National Death Index through 2019, for mortality ascertainment. A total of 47 individual social determinants of health were used to categorize participants in quartiles denoting increasing levels of social disadvantage. Poisson regression was used to report age-adjusted mortality rates across increasing social burden. Multivariable Cox proportional hazards models were used to assess the association between cumulative social disadvantage and all-cause mortality in adults with diabetes, adjusting for traditional risk factors. RESULTS: The final sample comprised 182 445 adults, of whom 20 079 had diabetes. In the diabetes population, mortality rate increased from 1052.7 per 100 000 person-years in the first quartile (Q1) to 2073.1 in the fourth quartile (Q4). In multivariable models, individuals in Q4 experienced up to twofold higher mortality risk relative to those in Q1. This effect was observed similarly across gender and racial/ethnic subgroups, although with a relatively stronger association for non-Hispanic white participants compared with non-Hispanic black and Hispanic subpopulations. CONCLUSIONS: Cumulative social disadvantage in individuals with diabetes is associated with over twofold higher risk of mortality, independent of established risk factors. Our findings call for action to screen for unfavorable social determinants and design novel interventions to mitigate the risk of mortality in this high-risk population.

Unfavorable social determinants of health and mortality risk by cardiovascular disease status: Findings from a National Study of United States Adults.

BACKGROUND: The association between cumulative burden of unfavorable social determinants of health (SDoH) and all-cause mortality has not been assessed by atherosclerotic cardiovascular disease (ASCVD) status on a population level in the United States. METHODS: We assessed the association between cumulative social disadvantage and all-cause mortality by ASCVD status in the National Health Interview Survey, linked to the National Death Index. RESULTS: In models adjusted for established clinical risk factors, individuals experiencing the highest level of social disadvantage (SDoH-Q4) had over 1.5 (aHR = 1.55; 95%CI = 1.22, 1.96) and 2-fold (aHR = 2.21; 95% CI = 1.91, 2.56) fold increased risk of mortality relative to those with the most favorable social profile (SDoH-Q1), respectively for adults with and without ASCVD; those experiencing co-occurring ASCVD and high social disadvantage had up to four-fold higher risk of mortality (aHR = 3.81; 95%CI = 3.36, 4.32). CONCLUSIONS: These findings emphasize the importance of a healthcare model that prioritizes efforts to identify and address key social and environmental barriers to health and wellbeing, particularly in individuals experiencing the double jeopardy of clinical and social risk.

Polysocial Risk Scores: Implications for Cardiovascular Disease Risk Assessment and Management.

PURPOSE OF REVIEW: To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiovascular health management. RECENT FINDINGS: Limited existing evidence suggests that pSRS are promising tools to capture cumulative social determinants of health (SDOH) burden and improve CVD risk prediction beyond traditional risk factors. However, available tools lack generalizability, are cross-sectional in nature or do not assess social risk holistically across SDOH domains. Available SDOH and clinical risk factor data in large population-based databases are under-utilized for pSRS development. Recent advances in machine learning and artificial intelligence present unprecedented opportunities for SDOH integration and assessment in real-world data, with implications for pSRS development and validation for both clinical and healthcare utilization outcomes. pSRS presents unique opportunities to potentially improve traditional "clinical" models of CVD risk prediction. Future efforts should focus on fully utilizing available SDOH data in large epidemiological databases, testing pSRS efficacy in diverse population subgroups, and integrating pSRS into real-world clinical decision support systems to inform clinical care and advance cardiovascular health equity.

Association Between Claims-Defined Frailty and Outcomes Following 30 Versus 12 Months of Dual Antiplatelet Therapy After Percutaneous Coronary Intervention: Findings From the EXTEND-DAPT Study.

Background Frailty is rarely assessed in clinical trials of patients who receive dual antiplatelet therapy (DAPT) after percutaneous coronary intervention. This study investigated whether frailty defined using claims data is associated with outcomes following percutaneous coronary intervention, and if there is a differential association in patients receiving standard versus extended duration DAPT. Methods and Results Patients ≥65 years of age in the DAPT (Dual Antiplatelet Therapy) Study, a randomized trial comparing 30 versus 12 months of DAPT following percutaneous coronary intervention, had data linked to Medicare claims (n=1326), and a previously validated claims-based index was used to define frailty. Net adverse clinical events, a composite of all-cause mortality, myocardial infarction, stroke, and major bleeding, were compared between frail and nonfrail patients. Patients defined as frail using claims data (12.0% of the cohort) had higher incidence of net adverse clinical events (23.1%) compared with nonfrail patients (10.7%; P<0.001) at 18-month follow-up and increased risk after multivariable adjustment (adjusted hazard ratio [HR], 2.24 [95% CI, 1.38-3.63]). There were no differences in effects of extended duration DAPT on net adverse clinical events for frail (HR, 1.42 [95% CI, 0.73-2.75]) and nonfrail patients (HR, 1.18 [95% CI, 0.83-1.68]; interaction P=0.61), although analyses were underpowered. Bleeding was highest among frail patients who received extended duration DAPT. Conclusions Among older patients in the DAPT Study, claims-defined frailty was associated with higher net adverse clinical events. Effects of extended duration DAPT were not different for frail patients, although comparisons were underpowered. Further investigation of how frailty influences ischemic and bleeding risks with DAPT are warranted. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT00977938.

Frailty and mortality associations in patients with COVID-19: a systematic review and meta-analysis.

BACKGROUND: Observational data during the pandemic have demonstrated mixed associations between frailty and mortality. AIM: To examine associations between frailty and short-term mortality in patients hospitalised with coronavirus disease 2019 (COVID-19). METHODS: In this systematic review and meta-analysis, we searched PubMed, Embase and the COVID-19 living systematic review from 1 December 2019 to 15 July 2021. Studies reporting mortality and frailty scores in hospitalised patients with COVID-19 (age ≥18 years) were included. Data on patient demographics, short-term mortality (in hospital or within 30 days), intensive care unit (ICU) admission and need for invasive mechanical ventilation (IMV) were extracted. The quality of studies was assessed using the Newcastle-Ottawa Scale. RESULTS: Twenty-five studies reporting 34 628 patients were included. Overall, 26.2% (n = 9061) died. Patients who died were older (76.7 ± 9.6 vs 69.2 ± 13.4), more likely male (risk ratio (RR) = 1.08; 95% confidence interval (CI): 1.06-1.11) and had more comorbidities. Fifty-eight percent of patients were frail. Adjusting for age, there was no difference in short-term mortality between frail and non-frail patients (RR = 1.04; 95% CI: 0.84-1.28). The non-frail patients were commonly admitted to ICU (27.2% (4256/15639) vs 29.1% (3567/12274); P = 0.011) and had a higher mortality risk (RR = 1.63; 95% CI: 1.30-2.03) than frail patients. Among patients receiving IMV, there was no difference in mortality between frail and non-frail (RR = 1.62; 95% CI 0.93-2.77). CONCLUSION: This systematic review did not demonstrate an independent association between frailty status and short-term mortality in patients with COVID-19. Patients with frailty were less commonly admitted to ICU and non-frail patients were more likely to receive IMV and had higher mortality risk. This finding may be related to allocation decisions for patients with frailty amidst the pandemic.

Assessment of s-nitrosothiol and thiol/disulfide levels in acute coronary syndrome patients.

BACKGROUND: The level of nitric oxide (NO) is important to protect the heart from ischemic damage in acute coronary syndrome (ACS) patients. S-nitrosothiol (SNO) is a molecule that represents the main form of NO storage in the vascular structure. In addition, dynamic thiol/disulfide homeostasis (TDH) is known to play an important role in maintaining the oxidant-antioxidant balance. In this study, our aim is to evaluate the oxidative/nitrosative stress status according to SNO level and TDH in patients with ACS. METHODS: The study included 124 patients who were admitted to the emergency service and 124 consecutive individuals who applied to the cardiology outpatient clinic with cardiac complaints and underwent coronary angiography (CAG). Blood was drawn from all participants included in the study to determine SNO, nitrite, total thiol, native thiol, and disulfide levels after 12 h of fasting. RESULTS: Serum SNO levels were found to be significantly lower in ACS patients compared to the control group (0.3 ± 0.08 vs. 0.4 ± 0.10 µmol/L, successively, p < 0.001). In addition, while the total thiol, native thiol, and native thiol/total thiol levels were lower in the patient group compared to the control group, nitrite, disulfide/native thiol and disulfide/total thiol levels were higher. As a result of multivariate logistic regression analysis, it was determined that age, gender, smoking, low-density lipoprotein cholesterol, glycosylated haemoglobin, and SNO levels were independent predictors in predicting ACS patients. DISCUSSION: S-nitrosothiol and thiol levels were found to be significantly lower in ACS patients. In addition, SNO molecule was independently associated with the presence of ACS diagnosis.

Association of entirely claims-based frailty indices with long-term outcomes in patients with acute myocardial infarction, heart failure, or pneumonia: a nationwide cohort study in Turkey.

BACKGROUND: Several countries have increasingly focused on improving care for acute myocardial infarction (AMI), heart failure (HF), and pneumonia to reduce their readmissions and mortality rates. Frailty is becoming increasingly important to accurately predict healthcare utilization for the aging population. The preferred method for the measurement of frailty remains unclear, and current risk-adjustment models do not account for frailty. We sought to compare commonly used frailty indices in terms of the ability to predict clinical adverse outcomes in AMI, HF, and pneumonia patients. METHODS: A nationwide cohort study included AMI, HF, and pneumonia with 65 years and older patients in the Turkey between January 1 and December 31, 2018. The primary predictor of interest was frailty. We used two claims-based frailty indices (Johns Hopkins Claims-Based Frailty Index and Hospital Frailty Risk Score) to assess frailty. The main outcome was all-cause long-term mortality up to 3 years. Time to death was calculated as the time period between the date of first admission and the date of death. Patients were censored as of September 30, 2020, which marked the end of the follow-up period. FINDINGS: Of the 200,948 patients, 35,096 (17.5%) had AMI, 62,403 (31.1%) had HF, and 103,449 (51.5%) had pneumonia. Johns Hopkins Claims-Based Frailty Index (c-statistics for long-term mortality: 0.68 in AMI, 0.61 in HF, 0.64 in pneumonia) was better compared to Hospital Frailty Risk Score (c-statistics for long-term mortality: AMI=0.62, HF=0.58, pneumonia=0.62) (DeLong p<0.001 in all). INTERPRETATION: Readmission and mortality rates after AMI, HF, and pneumonia gradually increases with increasing frailty score. While the Hospital Frailty Risk Score had a better discrimination for predicting readmissions, Johns Hopkins Claims-Based Frailty Index had a better discrimination for predicting mortality. These findings should be taken into account for a better evaluation of hospital performance. FUNDING: This study was supported by funding from The Scientific and Technological Research Council of Turkey (grant 120S422, HK).

The prognostic role of cardiac troponin in hospitalized COVID-19 patients.

BACKGROUND AND AIMS: Myocardial injury defined by elevation of cardiac troponins (cTn) in the course of coronavirus disease 2019 (COVID-19) pandemic has been reported, though not fully characterized yet. Using the Turkish nationwide centralized COVID-19 database, we sought to determine whether cTn measured within 24 h of admission may help identify 30-day all-cause mortality in hospitalized patients. METHODS: This retrospective cohort study was conducted at all hospitals in Turkey between March 11, 2020, and June 22, 2020. All hospitalized COVID-19 patients (≥18 years) who had cTn measurements within 24 h of admission were included. The primary outcome was 30-day all-cause mortality. RESULTS: A total of 14,855 COVID-19 patients (median age 49 years and 54% male) from 81 provinces of Turkey were included. Of these, 2020 patients (13.6%) were transferred to intensive care unit, 1165 patients (7.8%) needed mechanical ventilation, and 882 patients (5.9%) died during hospitalization. The prevalence of cTn positivity was 6.9% (n = 1027) in the hospitalized patients. cTn positivity was 5% in those patients alive at 30-day, and 44% in those who died. In multivariable Cox proportional hazard regression model, age, lactate dehydrogenase, and cTn were the strongest predictors of 30-day mortality, irrespective of cTn definition as a continuous, ordinal variable, or dichotomic variables. CONCLUSIONS: A single measurement of cTn at admission in patients with COVID-19 is associated with 30-day all-cause mortality and may have an important prognostic role for optimizing risk stratification.

Development and validation of clinical prediction model to estimate the probability of death in hospitalized patients with COVID-19: Insights from a nationwide database.

In the current study, we aimed to develop and validate a model, based on our nationwide centralized coronavirus disease 2019 (COVID-19) database for predicting death. We conducted an observational study (CORONATION-TR registry). All patients hospitalized with COVID-19 in Turkey between March 11 and June 22, 2020 were included. We developed the model and validated both temporal and geographical models. Model performances were assessed by area under the curve-receiver operating characteristic (AUC-ROC or c-index), R2 , and calibration plots. The study population comprised a total of 60,980 hospitalized COVID-19 patients. Of these patients, 7688 (13%) were transferred to intensive care unit, 4867 patients (8.0%) required mechanical ventilation, and 2682 patients (4.0%) died. Advanced age, increased levels of lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, creatinine, albumine, and D-dimer levels, and pneumonia on computed tomography, diabetes mellitus, and heart failure status at admission were found to be the strongest predictors of death at 30 days in the multivariable logistic regression model (area under the curve-receiver operating characteristic = 0.942; 95% confidence interval: 0.939-0.945; R2 = .457). There were also favorable temporal and geographic validations. We developed and validated the prediction model to identify in-hospital deaths in all hospitalized COVID-19 patients. Our model achieved reasonable performances in both temporal and geographic validations.

The role of Frailty on Adverse Outcomes Among Older Patients with COVID-19.

BACKGROUND: Diagnosis and screening of frailty, a condition characterized by an increased vulnerability to adverse outcomes of COVID-19, has emerged as an essential clinical tool which is strongly recommended by healthcare providers concerned with hospitalized elderly population. The data showing the role of frailty in patients infected with COVID-19 is needed. METHODS: This was a nationwide cohort study conducted at all hospitals in Turkey. All COVID-19 hospitalized patients (≥ 65 years) were included. Patients who were alive and not discharged up to July 20, 2020, were excluded. The frailty was assessed by using the "Hospital Frailty Risk Score" (HFRS). Patients were classified into three risk groups of frailty based on previously validated cut points as low (<5 points), intermediate (5-15 points), and high (>15 points). Additionally, patients who had the HFRS of ≥5 were defined as frail. The primary outcome was in-hospital mortality rates by frailty group. RESULTS: Between March 11, 2020, and June 22, 2020, a total of 18,234 COVID-19 patients from all of 81 provinces of Turkey were included. Totally, 12,295 (67.4%) patients were defined as frail (HFRS of >5) of which 2,801 (15.4%) patients were categorized in the highest level of frailty (HFRS of >15). Observed in-hospital mortality rates were 697 (12.0%), 1,751 (18.2%) and 867 (31.0%) in low, intermediate and high hospital frailty risk, respectively (p<0.001). Compared with low HFRS (<5), the adjusted odds ratios for in-hospital mortality were 1.482 (1.334-1.646) for intermediate HFRS (5-15) and 2.084; 95% CI, 1.799-2.413 for high HFRS (>15). CONCLUSIONS: As a claims-based frailty model, the HFRS provides clinicians and health systems, a standardized tool for an effective detection and grading of frailty in patients in COVID-19. A frailty-based tailored management of the older population may provide a more accurate risk categorization for both therapeutic and preventive strategies.

Whole blood viscosity predicts nondipping circadian pattern in essential hypertension.

Aim: We aimed to investigate the association between whole blood viscosity (WBV) and nondipping pattern in patients with essential hypertension. Materials & methods: A total of consecutive 530 patients who had been evaluated by ambulatory blood pressure monitoring were included. WBV was estimated by using hematocrit and plasma total protein levels for both WBV in low shear rate (0.5 s-1) and WBV in high shear rate (208 s-1) according to the de Simone's formula. Results: In the multivariate analysis, low shear rate and high shear rate of WBV were associated independently with nondipping pattern in patients with essential hypertension. Conclusion: As a simple, inexpensive and noninvasive tool, WBV seems to be a significant predictor of nondipping hypertension.

Relation of Frailty to Outcomes After Catheter Ablation of Atrial Fibrillation.

Catheter ablation for atrial fibrillation (AF) improves outcomes compared with medical treatment alone. Risk stratification for outcomes following AF ablation remains an important area of uncertainty. This analysis evaluated the association between frailty and outcomes following AF ablation. We evaluated US inpatients receiving AF ablation between January 1, 2016 and December 1, 2016 using Medicare fee-for-service billing codes. Diagnosis codes were used to calculate patients' Hospital Frailty Risk Score, with the cohort divided according to established cut-points of low (<5), intermediate (5 to 15), and high (>15) risk for frailty. The primary outcome was survival. Among 5,070 in patients treated with catheter ablation (mean age 74.9 ± 6.8 years, 51.1% female), 38.6% were defined as frail with a Hospital Frailty Risk Score >5, including 8.3% at high risk. Mortality rates (up to 630 days) were 5.8% in the low-risk group, 23.4% in the intermediate-risk group, and 42.2% in the high-risk group (log-rank p values <0.001 for comparison between categories). In restricted cubic spline regression analysis, the adjusted hazard ratios for long-term mortality monotonically increased with increasing values of the Hospital Frailty Risk Score (adjusted hazard ratio 1.065, 95% confidence interval 1.054 to 1.077). In secondary end points, frailty was independently associated with length of stay, postprocedure 30-day mortality, 30-day readmission and postdischarge 30-day mortality rates. In conclusion, frailty as assessed by a claims-based score is common in inpatient recipients of AF ablation, and provides risk stratification for mortality and other key clinical outcomes.

Association of Frailty With 30-Day Outcomes for Acute Myocardial Infarction, Heart Failure, and Pneumonia Among Elderly Adults.

Importance: The addition of a claims-based frailty metric to traditional comorbidity-based risk-adjustment models for acute myocardial infarction (AMI), heart failure (HF), and pneumonia improves the prediction of 30-day mortality and readmission. This may have important implications for hospitals that tend to care for frail populations and participate in Centers for Medicare & Medicaid Services value-based payment programs, which use these risk-adjusted metrics to determine reimbursement. Objective: To determine whether the addition of frailty measures to traditional comorbidity-based risk-adjustment models improved prediction of outcomes for patients with AMI, HF, and pneumonia. Design, Setting, and Participants: A nationwide cohort study included Medicare fee-for-service beneficiaries 65 years and older in the United States between January 1 and December 1, 2016. Analysis began August 2018. Main Outcomes and Measures: Rates of mortality within 30 days of admission and 30 days of discharge, as well as 30-day readmission rates by frailty group. We evaluated the incremental effect of adding the Hospital Frailty Risk Score (HFRS) to current comorbidity-based risk-adjustment models for 30-day outcomes across all conditions. Results: For 785 127 participants, there were 166 200 hospitalizations [21.2%] for AMI, 348 619 [44.4%] for HF, and 270 308 [34.4%] for pneumonia. The mean (SD) age at the time of hospitalization was 79.2 (8.9) years; 656 315 (83.6%) were white and 402 639 (51.3%) were women. The mean (SD) HFRS was 7.3 (7.4) for patients with AMI, 10.8 (8.3) for patients with HF, and 8.2 (5.7) for patients with pneumonia. Among patients hospitalized for AMI, an HFRS more than 15 (compared with an HFRS <5) was associated with a higher risk of 30-day postadmission mortality (adjusted odds ratio [aOR], 3.6; 95% CI, 3.4-3.8), 30-day postdischarge mortality (aOR, 4.0; 95% CI, 3.7-4.3), and 30-day readmission (aOR, 3.0; 95% CI, 2.9-3.1) after multivariable adjustment for age, sex, race, and comorbidities. Similar patterns were observed for patients hospitalized with HF (30-day postadmission mortality: aOR, 3.5; 95% CI, 3.4-3.7; 30-day postdischarge mortality: aOR, 3.5; 95% CI, 3.3-3.6; and 30-day readmission: aOR, 2.9; 95% CI, 2.8-3.0) and among patients with pneumonia (30-day postadmission mortality: aOR, 2.5; 95% CI, 2.3-2.6; 30-day postdischarge mortality: aOR, 3.0; 95% CI, 2.9-3.2; and 30-day readmission: aOR, 2.8; 95% CI, 2.7-2.9). The addition of HFRS to traditional comorbidity-based risk-prediction models improved discrimination to predict outcomes for all 3 conditions. Conclusions and Relevance: Among Medicare fee-for-service beneficiaries, frailty as measured by the HFRS was associated with mortality and readmissions among patients hospitalized for AMI, HF, or pneumonia. The addition of HFRS to traditional comorbidity-based risk-prediction models improved the prediction of outcomes for all 3 conditions.

Serum Sirtuin 1, 3 and 6 Levels in Acute Myocardial Infarction Patients.

BACKGROUND: Sirtuins may act in many cellular processes like apoptosis, DNA repair and lipid/glucose metabolism. Experimental studies suggested some sirtuin types may have protective effects against endothelial dysfunction, atherosclerosis, cardiac hypertrophy and reperfusion injury. Data about sirtuins in acute myocardial infarction (AMI) patients are scarce. OBJECTIVES: To investigate temporal changes of serum sirtuin 1,3 and 6 levels in AMI patients; to compare the serum sirtuin 1,3 and 6 levels between AMI patients and control subjects; and to investigate the association of serum sirtuin 1,3 and 6 levels with prognostic markers of AMI. METHODS: Forty patients with AMI and 40 patients with normal coronary arteries were included. Left ventricular ejection fraction (LVEF), serum proBNP, CRP, sirtuin1, sirtuin 3 and sirtuin 6 levels were processed. Peak troponin T levels, GRACE score, first day / second day sirtuin levels were recorded of AMI patients. A p value < 0.05 was considered statistically significant. RESULTS: Serum sirtuin 1,3 and 6 levels in AMI patients were similar to those in normal coronary patients. No temporal change in serum sirtuin 1,3 and 6 levels were found in AMI course. No correlation was evident between the sirtuin levels and the following parameters: proBNP, CRP, peak troponin and LVEF. Baseline sirtuin 1 and 6 levels were positively correlated with reperfusion duration. Baseline sirtuin 3 levels were negatively correlated with GRACE score. CONCLUSION: Serum sirtuin 1,3 and 6 levels in AMI patients were similar to those in normal coronary patients. This study does not represent evidence of the possible protective effects of sirtuin1, 3 and 6 in AMI patients.

Trends in isolated aortic valve replacement in the United States in the early phase of expansion of TAVR.

This study aimed to evaluate changes in volume, risk profile, and outcomes among elderly individuals undergoing isolated aortic valve replacement (AVR) after TAVR approval in the United States. Retrospective cohort study of patients ≥65 years old with at least one procedural code for isolated SAVR or TAVR among the Medicare beneficiaries between January 1, 2009 and December 31, 2014. A total of 137,563 hospitalizations for isolated AVR between 2009 and 2014 were included (SAVR: 102,968 [74.9%]; TAVR: 34,595 [25.1%]). Overall AVR volumes increased by 21.8% per year after TAVR introduction, compared with 2.3% prior (p ≪ 0.001). Changes in SAVR volumes were similar both before and after TAVR introduction, (2.3% per year growth before vs. 2.1% after, p = 0.24). Although patient risk profiles increased among the AVR population (predicted 30-day mortality 4.0% in 2009 vs. 5.4% in 2014; p for trend =0.048), observed 30-day mortality (4.0% in 2009 vs. 3.9% in 2014; p for trend =0.96) and 1-year mortality (10.8% in 2009 to 12.2% in 2014; p for trend =0.069) rates remained stable. Among elderly U.S. patients enrolled in the Medicare, the introduction and the dissemination in the early phase of TAVR was associated with an expansion of AVR to high risk patients, without an observed reduction in the use of SAVR. This expansion was associated with similar mortality among all AVR patients, despite an increase in patient risk.